Classification of Green Coffees by FT-IR Analysis of Dry Extract

Abstract

Principal component analysis (PCA) of infrared spectra has been used as a classification method for the green beans of coffee from various origin. Before spectral acquisition, sampling methods were tested for 45 samples, and we chose dry extract of water-soluble compounds on SiCaF₂ supports. After PCA of the first derivatized spectra, the first four loadings were examined. The scores of the second principal component appear to be directly correlated by their sign to the species arabica or robusta. This result allows an easy classification. In the same way, the pigmentation is well characterized into two groups on the scattergram of the samples with respect to the PC1 and PC3 components. Another feature of this method is that the analysis of the spectral data in terms of residual variance separate components which are correlated with properties. This approach provides assistance in the interpretation of infrared spectra of complex mixtures.